Download Tradeoffs in seedling growth and survival within and across tropical

Trade-offs in seedling growth and survival within and
across tropical forest microhabitats
Faith Inman-Narahari1, Rebecca Ostertag2, Gregory P. Asner3, Susan Cordell4, Stephen P. Hubbell1,5
& Lawren Sack1
1
Department of Ecology and Evolutionary Biology, University of California, 621 Charles E. Young Drive South, Los Angeles, California 90095-1606
Department of Biology, University of Hawaii, 200 W. Kawili Street, Hilo, Hawaii 96720
3
Department of Global Ecology, Carnegie Institution for Science, 260 Panama St., Stanford, California 94305
4
USDA Forest Service, Institute of Pacific Islands Forestry, 60 Nowelo Street, Hilo, Hawaii 96720
5
Center for Tropical Forest Science, Smithsonian Tropical Research Institute, Balboa, Republic of Panam
a
2
Keywords
Determinants of plant community diversity
and structure, light, performance rank
changes, plant population and community
dynamics, regeneration niche, relative growth
rate, substrate, survival, topography, tropical
forest diversity.
Correspondence
Faith Inman-Narahari, Komohana Research
and Extension Center, 875 Komohana St.,
Hilo, HI 96720.
Tel: (808) 969-8268;
Fax: (808) 933-8120;
E-mail: [email protected]
Funding Information
The National Science Foundation (Grants
EPSCoR 0554657 and IOS-0546784); the
Smithsonian Tropical Research Institute
Center for Tropical Forest Science; the
University of California, Los Angeles; the
University of Hawaii; and the USDA Forest
Service Pacific Southwest Research Station
Institute of Pacific Islands Forestry (USFS-IPIF)
provided financial and other essential
support.
Abstract
For niche differences to maintain coexistence of sympatric species, each species
must grow and/or survive better than each of the others in at least one set of
conditions (i.e., performance trade-offs). However, the extent of niche differentiation in tropical forests remains highly debated. We present the first test of
performance trade-offs for wild seedlings in a tropical forest. We measured
seedling relative growth rate (RGR) and survival of four common native woody
species across 18 light, substrate, and topography microhabitats over 2.5 years
within Hawaiian montane wet forest, an ideal location due to its low species
diversity and strong species habitat associations. All six species pairs exhibited
significant performance trade-offs across microhabitats and for RGR versus survival within microhabitats. We also found some evidence of performance
equivalence, with species pairs having similar performance in 26% of comparisons across microhabitats. Across species, survival under low light was generally
positively associated with RGR under high light. When averaged over all species, topography (slope, aspect, and elevation) explained most of the variation
in RGR attributable to microhabitat variables (51–53%) followed by substrate
type (35–37%) and light (11–12%). However, the relative effects of microhabitat differed among species and RGR metric (i.e., RGR for height, biomass, or
leaf area). These findings indicate that performance trade-offs among species
during regeneration are common in low-diversity tropical forest, although other
mechanisms may better explain the coexistence of species with small
performance differences.
Received: 6 May 2014; Revised: 4 July 2014;
Accepted: 13 July 2014
Ecology and Evolution 2014; 4(19): 3755–
3767
doi: 10.1002/ece3.1196
Introduction
Ecologists debate the extent to which partitioning of
regeneration niches, defined as differential performance of
seeds and seedlings across environmental gradients, contributes to plant species coexistence (Grubb 1977; Chesson 2000; Wright 2002; Hubbell 2009). One criterion for
niche differences to drive coexistence is that species must
change ranks in performance (i.e., growth or survival)
such that each species outperforms the others in at least
one habitat condition (performance trade-offs), leading to
differences in population growth rates among habitats
(Abrams 1983; Chesson 2000; Wright 2002). Additionally,
evidence has accumulated for a second type of trade-off,
ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use,
distribution and reproduction in any medium, provided the original work is properly cited.
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Seedling Trade-offs
F. Inman-Narahari et al.
between growth and survival within and across habitats.
For example, high relative growth rate (RGR) in high
resource environments (e.g., high light) is associated with
lower survival in low resource environments (e.g., low
light; Kitajima 1994; Walters and Reich 1999; Sack and
Grubb 2001; Wright et al. 2010). Some authors have
argued that performance trade-offs across habitats are
infrequent and make only a small contribution to tropical
forest community assembly relative to growth–survival
trade-offs because species’ performance and habitat differences are small (Kitajima and Bolker 2003). An alternative
hypothesis is that species within a community are functionally equivalent and that coexistence is maintained through
random birth and death (i.e., neutral theory; Hubbell
2001). When species are ecologically equivalent (i.e., neither
species outperforms the other in any situation; Hubbell
2001), “winners” at a particular site may be determined by
neutral or other mechanisms such as density dependence
(Janzen 1970; Connell 1971; Tilman 1994; Chesson 2000),
dispersal limitation, or priority effects (i.e., who arrives first;
Connell and Slatyer 1977; Urban and De Meester 2009).
Although the concept of trade-offs is a cornerstone of niche
theory, there remain very little data showing trade-offs for
any habitat variables other than light.
Few field-based studies have clearly demonstrated that
species differ in their regeneration niches such that seedlings change performance ranks (i.e., in RGR or survival)
across habitats. Differential species responses to environmental variation and habitat associations have been well
documented in tropical forests (e.g., Augspurger 1984;
Wright et al. 2003; Engelbrecht et al. 2007), but most of
these studies did not examine performance rank changes
across habitats. Other trade-off studies have examined
saplings or adult trees in the field (e.g., Pacala et al. 1994;
Davies 2001), experimentally manipulated seedlings in
greenhouses (e.g., Sack 2004), or employed experimental
plantings rather than naturally established seedlings (Ashton and Gunatilleke 1995; Kobe 1999; Montgomery and
Chazdon 2002; Baraloto et al. 2005; de Gouvenain et al.
2007). These data may not adequately represent adaptations of young plants in the wild (Bloor 2003; Cornelissen
et al. 2003). Our approach complements and builds on
previous studies of microhabitat trade-offs conducted
with seeded or transplanted seedlings, noting that there
are potential benefits and risks with either approach.
Direct seeding and transplanting are reasonable
approaches to looking at tradeoffs, especially once the
“natural” habitat conditions have been defined through
examination of wild populations. These methods have the
advantage of controlling and balancing sample sizes.
However, direct seeding and planting experiments risk
introducing bias by, for instance, seeding or planting into
sharply contrasting environments, such as very low versus
very high light. This may exaggerate observed differences
relative to the true differences shown by wild plants that
are typically dispersed across a more continuous range of
environmental conditions. Studies of wild seedlings may
better represent the natural dynamics of forest regeneration, but results in unbalanced sample sizes and may not
present clear contrasts among habitat conditions. We
present our approach as a method that could potentially
be employed by others given the existence of abundant
data from other forests that would allow similar analyses
(e.g., Comita and Engelbrecht 2009; Metz 2012).
We investigated performance trade-offs within and
across microhabitats for seedlings of four common woody
species in native-dominated Hawaiian montane wet forest.
To our knowledge, this is the first study to examine performance trade-offs across multiple habitat dimensions for
naturally established seedlings or for species in low-diversity tropical forest. We expected to find strong evidence of
performance trade-offs in seedlings of common species in
Hawaiian forest for four reasons. First, niche differences
are thought to be most apparent during early tree regeneration stages because seedlings are more sensitive to
environmental variation than adult trees (Grubb 1977;
Poorter 2007). Second, assuming they are well-mixed
spatially, common species interact with each other more
frequently than do rare species and are therefore hypothesized to be more likely to evolve niche differences in
response to interspecific competition (Hubbell 2006).
Third, niche differences may be the primary coexistence
mechanism in low-diversity forests because species interact
with a smaller number of competitors which allows for
niche displacement (as for common species) and because
other coexistence mechanisms, such as negative density
dependence and dispersal limitation, are predicted to be
weaker (Janzen 1971; Hurtt and Pacala 1995; Gravel et al.
2006), although few studies have investigated these
assumptions (Hille Ris Lambers et al. 2002; Johnson et al.
2012). Fourth, we measured multiple axes of microhabitat
variation (light, substrate, and topography) and multiple
growth variables (RGR for height, biomass, and leaf area)
to achieve a high power to resolve species differences (Russo et al. 2012). Because of their extreme isolation and
small land area, Hawaiian forests harbor fewer species than
most tropical forests of comparable climate and structure
(Carlquist 1985), thereby providing a unique model system
for testing hypotheses about niche differentiation and coexistence in a low-diversity tropical forest. In a previous
study, we showed that seedling distributions of common
species are strongly limited by establishment and show
strong habitat associations, suggesting that performance
differences would be likely (Inman-Narahari et al. 2013).
We focused on seedling responses to three environmental factors – light, topography, and substrate – because
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ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
F. Inman-Narahari et al.
these factors strongly affect plant growth and survival.
First, light is often the most limiting resource for plant
growth in tropical wet forests, and many studies demonstrate that plant species respond differentially to light gradients (e.g., Augspurger 1984; Kobe 1999; Sack and
Grubb 2001; Montgomery and Chazdon 2002; Poorter
and Arets 2003). Second, many plant species are strongly
associated with topographic gradients (Comita and Engelbrecht 2009; Metz 2012). Topography typically correlates
with essential plant growth resources such as soil moisture and nutrient availability with, for example, higher
soil moisture availability on slopes than plateaus (Becker
et al. 1988; Scowcroft and Jeffrey 1999; Daws et al. 2002;
Sørensen et al. 2006). Third, we expected substrate to be
an important axis of niche differentiation because many
tree species show strong habitat associations with organic
substrates such as logs and downed tree ferns; this is
especially common in Hawaiian wet forest where feral
ungulate soil disturbance is widespread (Cole et al. 2012;
Murphy et al. 2014).
This study addresses the following questions: (1) Do
species change ranks in their performance (RGR and survival) across habitats such that each species outperforms
each of the others under some set of conditions (microhabitat trade-offs)? (2) Do species’ RGR and survival
ranks change within and across microhabitats (growth–
survival trade-offs)? and (3) What is the relative
importance of topography (aspect, slope, and elevation),
light, and substrate microhabitats for seedling RGR?
Seedling Trade-offs
diameter at breast height (DBH, i.e., at 1.3 m) were
tagged, mapped, measured, and identified following
standard protocols applied throughout the CTFS plot
network (Condit 1998).
Data collection
We conducted this study in the 4 ha Laupahoehoe Forest
Dynamics Plot (FDP), part of the Hawaii Permanent Plot
Network (www.hippnet.hawaii.edu) and a member of the
Smithsonian Tropical Research Institute Center for Tropical Forest Science (CTFS) network. The Laupahoehoe
FDP is located on Hawaii Island (19°550 N, 155°170 W) in
the Laupahoehoe Hawaii Experimental Tropical Forest
(HETF). The FDP was established in 2008 at 1120 m elevation in native-dominated primary tropical lower montane wet forest (Holdridge 1947). The permanent plot is
located in one of the few places in Hawaii where native
forest dynamics can be studied because the presence of
non-natives in this part of the forest is remarkably low
and they are actively controlled. The Laupahoehoe FDP
comprises 21 native woody species, including three tree
fern species. The climate is largely aseasonal with
3440 mm mean annual rainfall (Giambelluca et al. 2013)
and 16°C mean annual temperature (Juvik and Juvik
1998). Within the FDP, all native woody species ≥1 cm
In October–December 2008, we established a grid of 192
1 m 9 1 m subplots within the 160 m 9 160 m central
area of the Laupahoehoe FDP following CTFS seedling
plot protocols (Wright et al. 2005; Fig. S1). Within subplots, we tagged all native woody species <1 cm DBH,
measured stem height from stem base to apex, and
counted the number of leaves, including cotyledons
(which are epigeal for these species). Measurements of
small seedlings in the forest are subject to substantial
error; thus, we rounded all measurements to the nearest
0.5 cm to equalize over- and underestimates. Following
our initial census in November–December 2008, we
remeasured previously tagged seedlings and measured
new seedlings four times over 2.5 years: in December
2009, July 2010, December 2010–January 2011, and July
2011.
We examined the four species that were sufficiently
abundant (N = 30–1461) within seedling plots to analyze
performance differences: Metrosideros polymorpha, Cheirodendron trigynum, Coprosma rhynchocarpa, and Vaccinium
calycinum (nomenclature follows Wagner et al. 1999; we
hereafter refer to these species by genus). These species
vary substantially in growth form: Metrosideros is the
dominant canopy tree in the Hawaiian Islands, Cheirodendron and Coprosma are midstory trees, and Vaccinium is
an understory shrub. These four species comprised 98%
of the seedlings found in seedling plots over the course of
the study. They also represent 22% of the 18 species and
58% of the relative abundance (RA) of native woody species that reach ≥1 cm DBH in the Laupahoehoe FDP
(Table 1; RA and number of individuals for each species
on each microhabitat category in Table S3).
To evaluate topography, we used a digital elevation
model (DEM) of the ground surface created by a smallfootprint, high-power airborne Light Detection and Ranging (LiDAR) system developed by the Carnegie Airborne
Observatory (Asner et al. 2007; Wu et al. 2012). For each
seedling plot, we extracted slope, aspect, and elevation
data from the DEM using the Spatial Analyst Tools in
ArcGIS 10.0 (ESRI, Redlands, CA). To quantify light, we
measured diffuse photosynthetically active radiation
(PAR, lmol photonsm2sec1) four times at each seedling plot (Fig. S2) and paired these measurements with
above-canopy PAR measurements to calculate transmitted
PAR (TPAR) for each seedling plot (Nicotra and Chazdon
1994; Montgomery and Chazdon 2002). To compare
ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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Materials and Methods
Study site
Seedling Trade-offs
F. Inman-Narahari et al.
Table 1. Information for the focal species analyzed in Hawaiian wet forest. Means SE with sample sizes in parentheses are shown. Species
sharing the same letter are not significantly different based on one-way ANOVA with Tukey’s HSD.”Wins” refers to the proportion of microhabitats in which each species performed significantly better than at least one other species.
Variable
Cheirodendron trigynum
Coprosma rhynchocarpa
Metrosideros polymorpha
Vaccinium calycinum
Family
Author
Species code
Habit
Tree RA (%)
Tree RD (%)
Tree RF (%)
Mean initial height of seedlings (cm)
N for RGR/survival1
Seedling LMA (gm2)2
RGRht wins
RGRpm wins
RGRla wins
Survival wins
Mean wins for all metrics
Araliaceae
(Gaudich.) A. Heller
CT
Midstory tree
27
6.2
10.2
2.9 0.04
633/1461
37A 2.9 (11)
0.04
0.22
0.00
0.02
0.07
Rubiaceae
A.Gray
CR
Midstory tree
7.9
0.87
10.1
3.81 0.11
153/342
30B 2.2 (14)
0.27
0.27
0.37
0.35
0.31
Myrtaceae
(H. L
ev.) H. St. John
MP
Canopy tree
21
38
10.2
0.87 0.04
807/1402
45C 4.6 (19)
0.69
0.80
0.55
0.41
0.61
Ericaceae
Sm.
VC
Understory shrub
2.1
0.049
5.23
4.04 0.54
30/49
43D 4.7 (7)
0.67
0.00
0.92
0.47
0.51
Relative abundance (RA = number of individuals of speciesi/number of individuals of all species 9 100), relative dominance (RD = basal area of
individuals of speciesi/basal area of all species 9 100), and relative frequency (RF = number of 20 9 20 m quadrates in which species was
recorded/total number of quadrates 9 100) are for trees ≥1 cm DBH within the 4 ha Laupahoehoe FDP.
1
Sample sizes were higher for survival than RGR because seedlings must have survived at least one census interval to calculate RGR.
2
Leaf mass per area (LMA = leaf mass/leaf area) calculated for seedlings harvested outside of FDP boundaries (N = 5–21 individuals per species).
RGR and survival of the four species across a variety of
microhabitat conditions, we distinguished three discrete
microhabitat categories (low, medium, and high) for the
following continuous environmental variables: slope, elevation, and TPAR. For aspect, we identified three major
categories using estimates of the proportion of land covered by each aspect (NE:0°-91°, SE-SW: 92°-242°, and
W-NW:242°-360°). We used categories for our analysis
rather than continuous variables because we did not
expect to find linear responses to these variables. We
recorded the rooting substrate of each seedling in six categories: live tree fern, dead tree fern, log, rock, root mat,
and soil. Logs, tree ferns, and root mats are important
rooting substrates for trees in Hawaiian forest (Santiago
2000). Detailed methods for topography and TPAR data
collection are in Appendix S1. Category values, means,
and variation in environmental conditions within the
4 ha FDP are in Appendix Table S1.
For each seedling, we calculated first year survival probability and three RGR metrics. Each metric provides
insight into a different aspect of plant performance
(Poorter et al. 2012). The first year survival probability is
the survival of each seedling (survived = 1, died = 0) for
the first year following the first measurement for that
seedling. Thus, the probability of survival was counted
only once for each seedling, only for the first year after it
was first tagged. The three RGR metrics were as follows:
(1) stem height RGR (RGRht, cmcm1year1); (2) whole
plant dry mass RGR (RGRpm, gg1 year1); and (3)
total leaf area RGR (RGRla, cm2cm2year1). We calculated RGR using the classic formula: RGR = (ln[final size]
– ln[initial size])/(final date-initial date) (Hoffmann and
Poorter 2002). Because relative and absolute growth rates
typically change with size (Poorter and Garnier 1996;
Paine et al. 2011), we equalized starting sizes by including
only individuals with initial heights below 10 cm (mean
initial heights for each species are listed in Table 1).
We used species-specific allometric equations to estimate total plant biomass (above- and below-ground)
and total plant leaf area from height and leaf counts
for seedlings in seedling plots (after Montgomery and
Chazdon 2002). We used whole plants harvested in the
nearby forest outside the FDP to develop allometric
equations to predict plant dry mass from height and to
predict total leaf area from both the number of leaves
and height. The R2 values were strong for regressions
of mass versus height (0.80–0.96) and for leaf area versus height and number of leaves (0.91–0.99; Table S2).
Detailed methods can be found in Appendix S1, regression equations are listed in Table S2, and plots of
predicted versus actual values are shown in Figure S4A
and B.
To test for RGR and survival differences among species
within each microhabitat category, we used generalized
linear mixed model analysis (GLMM) using the lme4 R
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ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
Analysis
F. Inman-Narahari et al.
package (Bates and Maechler 2009). For all models, we
included the subplot number as a random effect to
account for spatial autocorrelation (Comita et al. 2010).
Where the response variable was RGR, we used a Gaussian distribution, and where it was survival, we used a
binomial distribution (i.e., logistic regression). To examine differences among species within a given microhabitat,
we used Tukey’s tests with P-values corrected for multiple
comparisons using the Shaffer method in the multcomp R
package (Shaffer 1986; Hothorn et al. 2008). To calculate
mean RGR and survival for each species in each microhabitat category, we used the lsmeans R package (Lenth
2013) to calculate least squares means (LS-means) from
the results of GLMM analysis. LS-means are recommended to provide a unbiased estimate for unbalanced
designs (SAS OnlineDoc 1999). For comparisons of performance in each microhabitat, we averaged values across
all the other habitat categories (e.g., values for RGR for
seedlings growing on fallen logs were compared averaging
values for seedlings across all light and topography categories). Sample sizes would not permit analysis of species
on combinations of variables. For GLMM analyses, we
included species only where they were present in at least
three subplots in each microhabitat category. We converted survival LS-means from log-odds ratios to probabilities for tables and figures.
We used the results of GLMM analysis to test for (1)
microhabitat trade-offs for each species pair across microhabitats; (2) growth–survival trade-offs for each species
pair within a given microhabitat; and (3) trade-offs
between low-light survival and high-light RGR for each
species pair (using low and high TPAR values). For a
given species pair (e.g., species A vs. species B), where
species A had higher performance (RGR or survival) in a
given microhabitat than species B, we counted a “win”
for species A. If species A performed better in some microhabitats (i.e., “wins”) but species B “wins” other microhabitats, we counted that as a microhabitat trade-off.
Where we found no significant differences between species in a pair, we counted a “tie”. We counted a growth–
survival trade-off where species A “wins” for RGR but
species B “wins” for survival in a given microhabitat (or
vice versa). Finally, we scored a growth–survival trade-off
in high and low light if species pairs changed rank such
that species A had higher growth in high-light but lower
survival in low light than species B. Although species
pairs were not independent, we use the number of species
pairs with trade-offs to compare our results with other
studies because this is a measure that is, available from
most other studies on this topic.
To determine the effects of environmental factors on
RGR, we conducted relative importance analysis for the
contribution of topography, TPAR, and substrate. For this
ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
Seedling Trade-offs
analysis, we included initial height as a covariate (using
relaimpo R package; Lindeman et al. 1980; Grӧmping
2006). We conducted all statistical analyses using R 3.0.1
(R Core Team 2013).
Results
Differences among species across all
microhabitats
Relative growth rates and survival differed among species
when averaged across all microhabitats (Fig. 1). These differences were reflected in the overall proportion of microhabitats “won” by each species (Table 1). For example,
Vaccinium had the highest RGRla and survival and “won”
92% and 47% of microhabitats in species pair comparisons for RGRla and survival, respectively. Vaccinium also
had the lowest overall RGRpm and “won” no microhabitats in species pair comparisons. Likewise, Metrosideros
had the highest RGRpm and “won” 80% of microhabitats
for this RGR metric. Further, Cheirodendron had the lowest performance for all but RGRpm and also “won” fewer
habitats than the other species. Thus, overall performance
across all microhabitats was a reasonable indicator of
performance within each microhabitat.
Microhabitat trade-offs
We found substantial evidence for shifts in species’ relative performances across microhabitats for all six species
pairs (Question #1; Fig. 2, Table S3). Among the four
focal species, even the worst performing species outperformed the best performing species in at least one microhabitat for at least one performance metric (Fig. 2).
Further, all species pairs showed equivalence in at least
one microhabitat for at least one RGR metric (Fig. 2).
Indeed, the only species pair that showed no ties across
microhabitats was Cheirodendron and Vaccinium for
RGRht and RGRla.
Growth–survival trade-offs
All species pairs showed growth–survival trade-offs within
at least one microhabitat (Question #2; Fig. 3). Three to
five species pairs exhibited “win–lose” trade-offs. For
example, Cheirodendron had higher RGR but lower survival than Coprosma on logs. However, all species pairs
exhibited “win–tie” trade-offs. For example, species A had
higher survival than species B, but the species did not differ in either RGR or survival within a particular habitat.
We found little evidence of trade-offs between survival
in low TPAR and RGR in high TPAR. The general trend
was for species with high RGR in high TPAR to also have
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Seedling Trade-offs
(A)
(C)
F. Inman-Narahari et al.
(B)
(D)
(A)
(B)
(C)
(D)
high survival in low TPAR. However, for RGRpm, four of
six species pairs changed ranks between RGR in high
TPAR and survival in low TPAR (Fig. S5). For example,
Vaccinium had the highest survival in low TPAR of the
four species examined but had the lowest RGRpm in high
TPAR. For RGRht, only one of six species pairs changed
ranks between RGR in high TPAR and survival in low
TPAR, such that Metrosideros had higher RGRht in high
light than did Vaccinium, but lower survival in low TPAR
(Fig. S5).
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Figure 1. Mean relative growth rate (RGR)
and survival probabilities for the four focal
species averaged over all microhabitats in
Hawaiian wet forest, (A) height RGR; (B) leaf
area RGR; (C) dry mass RGR; and (D) survival;
error bars represent SE; species sharing the
same letter are not significantly different
(GLMM analysis); species codes and sample
sizes are in Table 1. Note: although the error
bars overlap for VC in panel D, the results of
the mixed model analysis indicate significant
differences.
Figure 2. Species performance trade-offs
across microhabitats for six species pairs of
four common species in Hawaiian wet forest;
bars represent the percent of microhabitats in
which each species had significantly higher
performance (A–C RGR and D survival) than
the other species in the pair (listed in order of
species 1 vs. species 2, e.g., MP vs. VC) and in
which neither species outperformed the other
(i.e., ties); analysis includes from 13 to 18 light,
substrate, and topography microhabitats with
sufficient numbers of seedlings of each
species; species codes and sample sizes are in
Table 1; detailed results in Appendix Table S4.
Relative importance of microhabitat factors
The relative importance of microhabitat factors varied by
RGR metric, although topography generally explained the
largest proportion of variance in RGR that was attributable to the microhabitat variables we measured (Question
#3; Fig. 4). Averaged over all species, the microhabitat
factors we measured explained 12–16% of the total variation in seedling RGR and initial height explained from
3% to 15%, depending on RGR metric. Of the variation
ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
F. Inman-Narahari et al.
Seedling Trade-offs
(A)
(B)
(C)
Figure 3. Growth–survival performance rank changes showing the proportion of microhabitats where RGR rank 6¼ survival rank for each growth
metric ((A)RGRht, (B)RGRpm, and (C)RGRla); win–lose situations are those in which the species with the highest RGR did not also have higher
survival or vice versa, win–tie situations are those in which one species in a pair had higher growth or survival, but did not differ from the other
species in the other metric (e.g., higher growth and not different survival); analysis includes from 13 to 18 light, substrate, and topography
microhabitats with sufficient numbers of seedling of each species; species codes and sample sizes are in Table 1; detailed results in Appendix
Table S4.
partitioned among microhabitat variables, topography
was the most important for all RGR metrics averaged
over all species (51–53%). The second-most important
factor was substrate (35–37%) followed by TPAR
(11–12%).
The relative importance of habitat factors also varied
among species. For example, topography explained 70–
75% of microhabitat variation in RGR for Cheirodendron
and Vaccinium, 43–44% of variation for Coprosma, and
only 22% for Metrosideros. Additionally, for Vaccinium,
the second-most important microhabitat variable differed
among RGR metrics, with TPAR being more important
than substrate for RGRht (17% vs. 10%) and RGRla (21%
vs. 9%), but with substrate being more important than
TPAR for RGRpm (12% vs. 17%). The relative importance
of topographic attributes (slope, elevation, or aspect) also
varied among species. Aspect was most important for
Cheirodendron, Coprosma, and Vaccinium (28–45%),
whereas elevation was most important for Metrosideros
(11–12%; Fig. 4).
There was a surprising amount of performance differentiation among species, despite the broad one-dimensional
habitat categories, suggesting that niches are important in
this forest. Five of six species pairs exchanged ranks for
mean RGR and/or survival in at least one microhabitat,
supporting predictions of shifting performance hierarchies
across habitats in low-diversity Hawaiian forest. In
addition, two species “won” relatively few microhabitat
categories (Coprosma and Cheirodendron) versus the other
two species (Metrosideros and Vaccinium), indicating
strong performance inequality between some species pairs.
However, the relative proportion of “wins” for each species was not reflective of their relative abundance within
the forest. Thus, it remains unclear whether these tradeoffs drive coexistence.
Another key finding was the importance of what may
be functional equivalence, represented as ties where neither species in a pair exhibited significant differences in
RGR or survival. Because there were few habitats in
which the poorest-performing species might “win” versus
better-performing species, neutral mechanisms, such as
priority effects and seed limitation (Chesson 2000; Hubbell 2001), may be more important for coexistence of
the poorly performing species. For example, Coprosma
was equivalent in performance to Vaccinium in 40% of
microhabitats. These results suggest that microhabitat
trade-offs at the regeneration stage occur in low-diversity
Hawaiian wet forest, but the coexistence mechanism of
some species pairs may be more likely due to random
processes given that they showed little differentiation,
whereas other species pairs may coexist via niche differences as they showed strong performance differences
across microhabitats. Further work is needed to determine the extent to which performance differences contribute to species coexistence. We found a larger
proportion of species pairs that differed in performance
across habitats in Hawaii than has been reported for
other forests by studies that used similar methods (Baraloto et al. 2005; Dent and Burslem 2009). For example,
a study in French Guiana found performance differences
across microhabitats for only three of 36 species pairs
of seedlings transplanted across light and soil treatments
ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
3761
Discussion
Strong performance differences across
microhabitats
Seedling Trade-offs
(A)
(B)
(C)
F. Inman-Narahari et al.
treatments (Dent and Burslem 2009). Other studies
employing different analyses have also shown species’
performance shifts across light levels, but did not quantify shifts by species pair (Agyeman et al. 1999; Sack
and Grubb 2001). One explanation for the large proportion of trade-offs in Hawaiian forest is that species in
low-diversity forests may be more likely to evolve niche
differences because interspecific interactions are more
predictable than in high-diversity forests (Hubbell 2006).
Previous trade-off studies were conducted in high-diversity forests where hundreds of tree species coexist,
whereas the forest where we conducted this study has
only 21 woody species. Due to the low species diversity
in Hawaiian forest, the four species we studied here represent a larger proportion of species diversity than in
previous studies of performance trade-offs that were
conducted in forests with higher species diversity. For
example, of the hundreds of tree species in lowland wet
forest in Costa Rica and French Guiana, Kobe (1999) and
Baraloto et al. (2005) focused on four and nine species,
respectively. Further, the species in this study all have low
to no seed limitation (Inman-Narahari et al. 2013); low
seed limitation is expected to increase the importance of
niche relative to neutral mechanisms by increasing the
potential for interspecific interactions (Hubbell 2001;
Gravel et al. 2006). Another explanation is that we
examined seedling responses to a larger number of habitat categories than most previous studies, which may
increase the potential for discovering trade-offs (Kitajima
and Poorter 2008; Philipson et al. 2011). In particular,
the high-resolution topographic data provided by airborne LiDAR add a unique level of detail for examining
species responses to topographic variation. These results
point to the necessity of measuring several habitat characteristics across a range of forest types to further
understand the extent of niche differentiation in tropical
forests.
Growth–survival trade-offs within
microhabitats
(Baraloto et al. 2005). Another study in Borneo found
no reversals for three species in a shade-house experiment comparing seedling growth across light and soil
We found substantial evidence of growth–survival tradeoffs within given microhabitats. In the aforementioned
study, only two of 36 species pairs showed “win–lose”
growth–survival trade-offs within the same microhabitat
(Baraloto et al. 2005). In our study, all species pairs exhibited “win–lose” growth–survival trade-offs. Comparing only
for height growth, which was the only measurement
reported by Baraloto et al. (2005), five of six species pairs
showed “win–lose” growth–survival trade-offs. These
growth–survival trade-offs often permitted the slower-growing species, (usually Cheirodendron or Coprosma), to “win”
versus the faster-growing species, (usually Metrosideros or
3762
ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
Figure 4. Relative importance of microhabitat characteristics for
predicting (A) height, (B) leaf area, and (C) mass RGR for four
common species in Hawaiian wet forest; calculated by partitioning R2
of generalized linear models after accounting for the effect of initial
size; topography variables (aspect, elevation, and slope) are stippled;
TPAR, transmitted photosynthetically active radiation.
F. Inman-Narahari et al.
Vaccinium) by having higher survival. It appears that
growth–survival trade-offs within microhabitats may be
an important mechanism promoting coexistence and
should be more widely investigated.
Growth–survival trade-offs across light
microhabitats
When examined across microhabitats, we found some evidence of trade-offs between RGR in high light versus survival in low light. The proportion of species pairs with
trade-offs in Hawaiian forest was high relative to other
forests for RGRpm, similar to other forests for RGRht, and
lower relative to other forests for RGRla. For example,
Augspurger (1984) in Panama, Kobe (1999) in Costa
Rica, and Baraloto et al. (2005) in French Guiana found
high-light RGR versus low-light survival trade-offs for
14%, 33%, and 22% of species pairs, respectively. In our
study, four of six species pairs showed a negative correlation between high-light RGRpm versus low-light survival
(60%), but only one pair showed such trade-offs for
RGRht and none for RGRla. The results for RGRpm are
consistent with the theory of a general trade-off in physiological capabilities between shade tolerators and light
demanders (Kitajima 1994; Sack and Grubb 2001; Kitajima and Poorter 2008), but results for the other growth
metrics do not support this theory.
Seedling Trade-offs
in Panama (R€
uger et al. 2011). For the dominant canopy
species, Metrosideros, substrate type was the most important microhabitat variable. Disconcertingly, the substrate
type on which Metrosideros had the lowest RGR and survival was dead tree ferns, on which they are frequently
found growing (Inman-Narahari et al. 2013). The relative
importance of microhabitat factors requires more investigation to understand how plant available resources vary
with topography and substrate and the physiological
mechanisms by which these resources affect seedling RGR
in forests.
Performance metrics matter
The relative importance analysis showed that substrate
type and topographic variables were important determinants of growth rates for these species. Topography, especially slope and aspect, was the most important
environmental variable for predicting seedling RGR for
most species. Slope and aspect strongly affect forest soil
resources (e.g., moisture and nutrients), temperature, and
litter thickness (Daws et al. 2002; John et al. 2007), which
in turn strongly and differentially influence species growth
(Palmiotto et al. 2004; Engelbrecht et al. 2007; Metz
2012). The relative importance of topography suggests
that soil resources and other factors associated with
topography are stronger drivers of seedling RGR than
either light or substrate for most species in this forest.
Light was less important in this forest, but we include it
for comparative purposes as it is an important factor in
many other forests and is one of the environmental variables most frequently investigated. The relatively weak
role of light in explaining seedling RGR is consistent with
the relatively higher understory light in Hawaiian forests
(Inman-Narahari et al. 2013) and with a recent study
reporting that light availability explained <12% of variation in tree growth rates within a lowland tropical forest
An important finding of this study was that interpretations of habitat trade-offs can depend on which performance metrics are measured. We included the three
growth metrics to provide a better understanding of the
ways in which plant growth differs for these species under
the various habitat conditions we examined. Height
growth (the most commonly measured variable for most
seedling studies) provides information about growth only
in one dimension, whereas plants actually grow in multiple dimensions. For example, leaf area growth may be
more reflective of plant adaptations to low light in the
forest understory, and biomass growth is indicative of
mass balance of the whole plant, including the roots.
Although we accept that our modeled approach is imperfect, it still provides intriguing clues that these variables
should be considered, rather than strict reliance on height
growth measurements, as is commonly performed. For
example, if we had restricted our analysis to only leaf area
RGR, we would have found microhabitat performance
tradeoffs for only one of the six species pairs. Instead, we
found 3/6, 2/6, 1/6, and 4/6 species pairs that had tradeoffs for RGR height, RGR mass, RGR leaf area, and survival, respectively. Similarly, a recent study in tropical
China found trade-offs for mass but not height growth
metrics (Yang et al. 2011), and an experiment on seedling
responses to regional environmental gradients in Panama
found stronger responses for leaf area than height
(Brenes-Arguedas et al. 2010). We found the most microhabitat performance tradeoffs for survival. To our knowledge, this is the first time that three different RGR
metrics and survival have been used to analyze species
performance differences across microhabitats. The fact
that all these variables are examined less frequently in
studies of performance differences across habitats might
partially explain the large proportion of trade-offs found
in this study compared with previous research (Kobe
1999; Baraloto et al. 2005; Dent and Burslem 2009).
Different performance metrics may provide different
insights into plant population dynamics. For example,
ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
3763
Relative importance of microhabitat factors
Seedling Trade-offs
rapid height growth may lead to increased light interception and eventually contribute to competitive dominance
where vertical light gradients are very steep (Givnish
1982). However, leaf area growth can likewise increase
light interception and correspond to photosynthetic area
for potential carbon gain (Koyama and Kikuzawa 2009).
This may be more important for small seedlings because
their growth is more restricted by their ability to acquire
limited resources in the understory than by direct competition with one another (Paine et al. 2008). Although the
relationships between plant growth and population
growth rates are unclear, we expect that, all else being
equal, high survival would be closely correlated with high
population growth rates. Given the importance of
growth–survival trade-offs, survival appears to be an especially important performance metric to elucidate niche
differentiation. As each metric may potentially vary in
importance for different aspects of a species’ performance,
the most comprehensive approach is to measure several
aspects of plant performance to determine interspecific
differences.
Caveats regarding coexistence
Our findings indicate that differential responses to microhabitats during regeneration in low-diversity tropical
forest fulfill the theoretical requirements of niche differentiation, a mechanism that may contribute to species
coexistence. However, making inferences about community assembly and coexistence based on seedling performance data remains challenging, especially given that
seedlings provide information on only a short span of a
trees’ lifetime. Nevertheless, some trade-off patterns were
consistent with the observed species relative abundance
in the Laupahoehoe FDP. For example, Metrosideros had
higher RGR than the three other species examined in
the majority of conditions, consistent with it being the
dominant canopy tree in this Hawaiian montane wet
forest (Asner et al. 2009; Vitousek et al. 2009). On the
other hand, Cheirodendron, a midstory tree species with
lower RGR, had higher relative abundance within the
4 ha plot than did Metrosideros (Table 1), suggesting
that adult size differences may be an aspect of significant
niche differentiation which occur at later life stages that
our analysis did not take into account (Baraloto et al.
2005). Though impractical for this study due to our
sample sizes, further examination of seedling trade-offs
could consider seedling RGR under combinations of
given factors (e.g., on logs in high TPAR versus logs in
low TPAR). Nevertheless, our data support the concept
that niche differentiation, in concert with other
mechanisms, is a potential contributor to patterns of
forest dominance for endemic tree species in Hawaiian
3764
F. Inman-Narahari et al.
montane wet forest. Future work is needed to clarify
whether niche mechanisms primarily determine coexistence among the strongest competitors with neutral or
other mechanisms being more important for coexistence
among the least competitive species.
Acknowledgments
We are grateful for substantial help from numerous field
assistants, including K. Nelson-Kaula, M. Murphy, R.
Moseley, K. Wailani-Nihipali, and others with the Hawaii
Community College Tropical Forest Ecosystem and
Agroforestry Management program and University of
Hawaii at Hilo Pacific Internship Programs for Exploring
Science programs. B. Hwang, M. Nullet, P. Scowcroft,
and J. Schulten provided invaluable logistical assistance.
The National Science Foundation (Grants EPSCoR
0554657 and IOS-0546784); the Smithsonian Tropical
Research Institute Center for Tropical Forest Science; the
University of California, Los Angeles; the University of
Hawaii; and the USDA Forest Service Pacific Southwest
Research Station Institute of Pacific Islands Forestry
(USFS-IPIF) provided financial and other essential support. We thank USFS-IPIF and the Hawaii Division of
Forestry and Wildlife/Department of Land and Natural
Resources for access to the Hawaii Experimental Tropical
Forest. The Carnegie Airborne Observatory is made possible by the Gordon and Betty Moore Foundation, John D.
and Catherine T. MacArthur Foundation, Grantham
Foundation for the Protection of the Environment, W.
M. Keck Foundation, Margaret A. Cargill Foundation,
Mary Anne Nyburg Baker and G. Leonard Baker Jr.,
and William R. Hearst III. Finally, we thank C. Giardina,
N. Inman-Narahari, T. Paine, W. Carson, D. J. Johnson,
and an anonymous reviewer for insightful comments.
Conflict of Interest
None declared.
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Seedling Trade-offs
Supporting Information
Additional Supporting Information may be found in the
online version of this article:
Appendix S1. Additional details on data collection and
analysis methods.
Table S1. Microhabitat factors across the 4-ha Forest
Dynamics Plot (FDP) in Hawaiian wet forest with
mean SE, range and percent cover within categories.
Table S2. Allometric equations and results of linear
regression analysis used for estimating plant dry mass and
leaf area for seedlings in forest plots in Hawaiian wet forest; mean values and ranges of harvested seedlings used
for regressions; for each species, we harvested 8–20 individuals across a range of sizes (0.85–63 cm) and light
habitats (1.7–15%; mean: 5.0%) corresponding to those
found in seedling plots.
Table S3. Number of seedlings and relative abundance
(RA) for each species in each microhabitat category.
Table S4. (A–D) Differences among species in relative
growth rates (RGR) and survival probability on each habitat category calculated with least squares means (Means)
and standard errors (SE) from GLMM analysis.
Figure S1. (A) Schematic of census station locations
within the 4-ha forest dynamics plot in Hawaiian native
forest, and (B) diagram of a census station with three
1-m2 seedling subplots within 2 m of a 0.5-m² seed trap.
Figure S2. Mean TPAR at each census interval in Hawaiian wet forest, letters based on Tukey’s HSD analysis of
repeated measures ANOVA; error bars represent SE,
TPAR mean (6.4%) and SE over all four censuses represented by dashed horizontal line and represented by dotted horizontal lines, respectively.
Figure S3. For each species, left plot shows natural log
transformed height data over time (days since first measurement) and right plot shows natural log transformed
mean heights versus mean days at each census (N = 5
censuses). Solid lines represent log-linear models and
dashed lines represent lowess smoothed lines. Model fits
show that log-linear models provide a reasonable approximation of growth for seedling species over the time period examined here.
Figure S4. (A, B) Scatter plots of actual versus predicted
plant mass of seedlings used for allometric equations (see
Table S2 for full equations).
Figure S5. Trade-offs between RGR in high TPAR and
survival in low TPAR showing species rank changes in
each category (species abbreviations as in Table 1).
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